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% Full title of the paper (Capitalized)
\Title{Epidemic features of coronavirus disease 2019 in Guangdong}

% Authors, for the paper (add full first names)
\Author{Li Jiachun$^{1,2,\ddagger,*}$\href{https://orcid.org/0000-0003-3293-2315}{\orcidicon}}

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% Affiliations / Addresses (Add [1] after \address if there is only one affiliation.)
\address{%
$^{1}$ \quad Sichuan University - Institute for Disaster Management and
Reconstruction Chengdu. 122, 610207 Sichuan, China; \href{mailto:sculjc@stu.scu.edu.cn}{\nolinkurl{sculjc@stu.scu.edu.cn}}\\
}
% Contact information of the corresponding author
\corres{Correspondence: \href{mailto:idmr214@126.com}{\nolinkurl{idmr214@126.com}}; Tel.:
+86-188-1007-6646.}

% Current address and/or shared authorship
\firstnote{Chengdu. 122, 610207 Sichuan, China}







% The commands \thirdnote{} till \eighthnote{} are available for further notes

% Simple summary

% Abstract (Do not insert blank lines, i.e. \\)
\abstract{The prevalence of coronavirus disease 2019 (COVID-19) from 2020-01-19 in
Guangdong Province was summarized and analyzed to understand the
prevalence of COVID-19 epidemic in cities of Guangdong Province. We
obtained COVID-19 epidemic data from various epidemic data release
platforms, analyzed the prevalence characteristics of the disease in
each city of Guangdong Province, and used R to map the spatial
distribution of the number of confirmed patients and incidence rate in
each city of Guangdong Province. It was found that the first confirmed
case of COVID-19 appeared on 2020-01-19 and reached the growth platform
on 2020-02-16 in Guangdong Province. As of 2020-07-26 Guangdong province
has a total of more than 1,600 patients with disease, which is in the
upper middle level in China, and the cure rate is higher than the
national average cure rate. The top three cities with the highest number
of confirmed cases are Guangzhou, Shenzhen and Zhuhai. The top three
cities with the highest incidence rates are Zhuhai, Guangzhou, and
Shenzhen, respectively. The progress of the epidemic in Guangdong
Province is relatively stable. Each city has implemented prevention and
control policies according to its own situation and basically stabilized
the epidemic in a controllable range.}

% Keywords
\keyword{coronavirus disease 2019; spatial distribution; Guangdong
Province;epidemic characteristic}

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\begin{document}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\hypertarget{introduction}{%
\section{Introduction}\label{introduction}}

Since late December 2019 caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2) coronavirus disease 2019 (coronavirus disease
2019. The outbreak of SARS-CoV-2 (COVID-19) in Wuhan has attracted
widespread attention from all sectors of the community since the
outbreak. The SARS-CoV-2 is a member of the coronavirus family,
following the severe acute respiratory syndrome coronavirus (SARS-CoV)
and the Middle East respiratory syndrome coronavirus (MERS-CoV). This is
the third coronavirus to cause severe pneumonia after the respiratory
syndrome coronavirus (MERS-CoV) \citep{Munster_2020, Perlman_2020}. The
reported basic reproduction index (R0) of SARS-CoV-2 is about 3.28
\citep{Liu_2020}. The main transmission routes of COVID-19 can be
identified as close airborne direct transmission, aerosol transmission
and contact transmission, and its impact has greatly exceeded that of
SARS-CoV in 2003 \citep{Liu_2020}. Isolating the infectious route is
currently considered the most effective means of prevention and control
\citep{Joel_2020}. As of 2020-07-26, the number of SARS-CoV-2 infections
has far exceeded the number of SARS-CoV infections in 2003, and the
cumulative number of diagnosed patients nationwide has reached 86839.
Guangdong, as a populous province, launched a first-level response to
major public health emergencies on January 23, 2020. All major medical
units in the province entered into epidemic readiness and quickly
developed a consensus of experts related to diagnosis and treatment
\citep{Tian_2020}. Since the outbreak of the epidemic, major news media
have continued to pay attention to the situation and made timely
information about the epidemic public\citep{Kooraki_2020}. The Guangdong
Provincial Health and Wellness Commission has continued to publish daily
outbreak-related data on the province since January 23, 2020. By
February 24, 2020, with the outbreak largely under control in Guangdong,
the response level in Guangdong Province was lowered. This study
analyzes and summarizes the prevalence of COVID-19 in the cities under
the jurisdiction of Guangdong Province with the data that can be
collected so far, and compares it with some national data.

\hypertarget{materials-and-methods}{%
\section{Materials and Methods}\label{materials-and-methods}}

\hypertarget{data-sources}{%
\subsection{Data sources}\label{data-sources}}

All data were obtained from the National Health and Wellness Commission
and the Hunan Provincial Health and Wellness Commission through official
channels, which were used to calculate the time trend and spatial
distribution of the epidemic in the 34 provincial administrative regions
of China, as well as the total number of provinces and the 21 cities in
the province, respectively. The starting and ending times are from
2020-01-19 to 2020-07-26. The data on the resident population of
Guangdong cities used are from the Guangdong Statistical Yearbook 2019

\hypertarget{type-of-data-and-calculation-of-indicators}{%
\subsection{Type of data and calculation of
indicators}\label{type-of-data-and-calculation-of-indicators}}

The diagnostic criteria for cases were determined according to the
requirements of the ``Diagnostic and Treatment Plan for Pneumonia with
Novel Coronavirus Infection (Trial Seventh Edition)'' issued by the
National Health Commission \citep{Wu_2020}, based on descriptive
epidemiological methods, and data collected included the cumulative
number of patients diagnosed, the cumulative number of patients who
died, and the cumulative number of patients who were cured. Calculated
metrics were population morbidity, mortality, and cure rates.
Statistical description of the collected information related to the
epidemic was performed.

\hypertarget{statistical-processing}{%
\subsection{Statistical processing}\label{statistical-processing}}

Use R to initially organize the data and form a data set. Use the
ggplot2 plug-in package to plot the spatial distribution of the
cumulative number of patients diagnosed with COVID-19 and the cumulative
incidence rate in Guangdong Province, and perform statistical analysis.

\hypertarget{results}{%
\section{Results}\label{results}}

\hypertarget{diagnosed-patients-and-morbidity-rate}{%
\subsection{Diagnosed patients and morbidity
rate}\label{diagnosed-patients-and-morbidity-rate}}

Among the 21 cities in Guangdong Province, Guangzhou and Shenzhen had
the most significant increase in the number of confirmed COVID-19
patients. Guangzhou has the highest number of diagnosed patients, with
the growth rate slowing down on April 20, 2020, and maintaining a slight
increase after this date due to the continued import of cases from
abroad. The second highest number of confirmed patients is in Shenzhen,
which reached a growth platform on April 29, 2020, with a cumulative
total of 462 confirmed patients and no new confirmed patients. The rest
of the cities are Guangzhou ( 586 ) , Shenzhen ( 462 ) , Zhuhai ( 105 )
, Dongguan ( 100 ) , Foshan ( 100 ) , Zhongshan ( 69 ) , Huizhou ( 62 )
, Shantou ( 26 ) , Jiangmen ( 24 ) , Zhanjiang ( 24 ) , Zhaoqing ( 20 )
, Meizhou ( 17 ) , Maoming ( 14 ) , Yangjiang ( 14 ) , Qingyuan ( 12 ) ,
Jiayang ( 11 ) , Shaoguan ( 10 ) , Chaozhou ( 6 ) , Heyuan ( 5 ) ,
Shanwei ( 5 ) , Yunfu ( 0 ) , (Figure 1) in order of the cumulative
number of diagnosed patients. The incidence rate of each city was
calculated according to the resident population of each city, with the
unit of Zhuhai ( 5.552 ) , Guangzhou ( 3.932 ) , Shenzhen ( 3.547 ) ,
Zhongshan ( 2.085 ) , Huizhou ( 1.284 ) , Foshan ( 1.265 ) , Dongguan (
1.192 ) , Yangjiang ( 0.548 ) , Jiangmen ( 0.522 ) , Zhaoqing ( 0.482 )
, Shantou ( 0.461 ) , Meizhou ( 0.388 ) , Shaoguan ( 0.334 ) , Zhanjiang
( 0.327 ) , Qingyuan ( 0.31 ) , Chaozhou ( 0.226 ) , Maoming ( 0.222 ) ,
Jiayang ( 0.181 ) , Shanwei ( 0.167 ) , Heyuan ( 0.162 ) , Yunfu ( 0 ) ,
as ``1/100,000'' (Figure 2).

\begin{figure}[H]
\centering
\includegraphics[width=10 cm]{D:/R_2020/DIBD-Paper/covid-19/confirmed_figure.pdf}
\caption{Spatial distribution of cumulative confirmed COVID-19 patients in prefecture-level cities (autonomous prefecture) of Guangdong Province}
\end{figure}

\begin{figure}[H]
\centering
\includegraphics[width=10 cm]{D:/R_2020/DIBD-Paper/covid-19/confirmed_rate_figure.pdf}
\caption{Spatial distribution of cumulative incidence rate in prefecture-level cities (autonomous prefecture) of Guangdong Province}
\end{figure}

The cumulative number of confirmed patients in the whole province was
1672, except for Yunfu city without confirmed cases, all the other
cities in Guangdong province were growing, with Guangzhou and Shenzhen
city growing sharply, reaching the growth platform stage around
mid-April. The rest of the cities had a similar trend of growth,
reaching the growth platform period around mid to late February (Figure
3).

\begin{figure}[H]
\centering
\includegraphics[width=12 cm]{D:/R_2020/DIBD-Paper/covid-19/city_confirmed_figure.pdf}
\caption{Time trend of cumulative confirmed COVID-19 patients in cities of Guangdong Province}
\end{figure}

\hypertarget{patients-who-died-and-their-mortality-rates}{%
\subsection{Patients who died and their mortality
rates}\label{patients-who-died-and-their-mortality-rates}}

As of 2020-07-26, Guangdong Province had a total of 8 COVID-19 patients,
respectively Shenzhen ( 3 ) , Dongguan ( 1 ) , Guangzhou ( 1 ) ,
Shaoguan ( 1 ) , Zhaoqing ( 1 ) , Zhuhai ( 1 ) , death rate (cumulative
number of dead patients / cumulative number of diagnosed patients) was
0.478 \%, while the national average death rate was 5.365 \%. The case
fatality rate in Guangdong Province was significantly lower than the
national level. The COVID-19 mortality rates in the 34 provincial
administrative regions of China are shown in (Figure 4).

\begin{figure}[H]
\centering
\includegraphics[width=15 cm]{D:/R_2020/DIBD-Paper/covid-19/province_dead_rate_figure.pdf}
\caption{Cumulative mortality rate of confirmed COVID-19 patients in the 34 province regions of China}
\end{figure}

\hypertarget{patients-cured-discharged-and-their-cure-rate}{%
\subsection{Patients cured (discharged) and their cure
rate}\label{patients-cured-discharged-and-their-cure-rate}}

As of 2020-07-26, a total of 1642 cases of cured and discharged patients
in Guangdong Province, of which, Guangzhou ( 565 ) , Shenzhen ( 459 ) ,
Zhuhai ( 102 ) , Foshan ( 100 ) , Dongguan ( 99 ) , Zhongshan ( 69 ) ,
Huizhou ( 62 ) , Shantou ( 26 ) , Jiangmen ( 24 ) , Zhanjiang ( 24 ) ,
Zhaoqing ( 19 ) , Meizhou ( 17 ) , Maoming ( 14 ) , Yangjiang ( 14 ) ,
Qingyuan ( 12 ) , Jiayang ( 11 ) , Shaoguan ( 9 ) , Chaozhou ( 6 ) ,
Heyuan ( 5 ) , Shanwei ( 5 ) , Yunfu ( 0 ) , The cure rate is 98.206 \%,
and the cure rate of COVID-19 in the 34 provincial administrative
regions of China is shown in (Figure 5).

\begin{figure}[H]
\centering
\includegraphics[width=15 cm]{D:/R_2020/DIBD-Paper/covid-19/province_cured_rate_figure.pdf}
\caption{Cumulative cure rate of confirmed COVID-19 patients in the 34 province regions of China}
\end{figure}

\hypertarget{discussions}{%
\section{Discussions}\label{discussions}}

As the largest province in China in terms of population, the growth of
confirmed cases in Guangdong Province, the largest province in China in
terms of epidemic time trends, is generally consistent with other
provinces in the country. With the exception of Guangzhou and Shenzhen,
where the growth was dramatic, the growth trend of the epidemic was
close to the same in all cities in Guangdong Province. Since the first
case, the cumulative number of confirmed cases continued to grow, and
quickly spread throughout the province, reaching a growth platform in
3-4 weeks. This is an important sign that the epidemic is largely under
control. The largest number of patients diagnosed in Guangdong Province
was in Guangzhou, followed by Shenzhen. The number of infections was
much higher than in other cities in the province, indicating a strong
correlation between the number of clusters and the cumulative number of
patients diagnosed. There were no confirmed cases in Yunfu City, which
is located in the northwest of Guangdong Province. Guangzhou and
Shenzhen, as two supercities, are densely populated with a dozen mobile
populations, and thus are severely affected by the epidemic in the
province, and this data is consistent with the demographic and
geographic factors of the epidemic epidemic \citep{Petrosillo_2020}. In
conclusion, it is important to adopt strict control measures in the
province.

As of 2020-07-26, Guangdong Province COVID-19 confirmed patient deaths
was 8 cases, respectively, Shenzhen ( 3 ) , Dongguan ( 1 ) , Guangzhou (
1 ) , Shaoguan ( 1 ) , Zhaoqing ( 1 ) , Zhuhai ( 1 ) , which is also the
province's infection cumulative number of confirmed patients in several
cities. The overall death rate of COVID-19 infection in Guangdong
Province was 0.478 \%, which was much lower than the national average
(0.90\%), which indirectly indicates that Guangdong Province has been
effective in the prevention of COVID-19 infection.

With the epidemic under effective control, Guangdong Province lowered
the response level for major public health emergencies on 24 February
2020. The overall cure rate of COVID-19 in Guangdong Province was 98.206
\%, which was higher than the national average 93.102 \%. Although the
peak of the COVID-19 epidemic in China has passed, many countries around
the world are facing increasing pressure to prevent and control the
epidemic. In Guangdong Province, the main task at this stage is to
strengthen the prevention and control of out-of-province and
out-of-country patients to prevent the resurgence of COVID-19. It is
also necessary to be alert to the possibility that some asymptomatic
patients in hiding may become potential sources of infection, and
therefore surveillance of the epidemic should not be relaxed.

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